Modern computer systems process large amounts of data. If there is a problem in the data or in the software used to process the data, then any downstream processes will be affected negatively. It is important to detect those problems as soon as possible to return the computer system to its properly functioning state. If those downstream processes support end-users, then early detection is even more imperative.
Detecting a problem in a computer system may be accomplished by detecting an anomaly in the data that the computer system processes. However, when an anomaly in data is identified, the anomaly might not reflect an error or problem at all. Instead, many anomalies reflect changes in natural user interaction with the computer system. For example, many users might visit a website during traditional after work hours, while the website might not experience much traffic during work hours. Therefore, notifying a system administrator of non-issues would waste the system administrator's time. Also, too many notifications of non-problem anomalies might cause a system administrator to ignore future anomalies that represent legitimate computer problems.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.